1. Field of the Invention
The present invention relates to an ultrasonic image processing apparatus for processing ultrasonic image signals obtained by transmitting ultrasonic waves and receiving ultrasonic echoes, an ultrasonic image processing method to be used therein, and an ultrasonic image processing program for allowing a CPU to execute such ultrasonic image processing.
2. Description of a Related Art
In medical fields, various imaging technologies have been developed in order to observe the interior of an object to be inspected and to make diagnoses. Especially, ultrasonic imaging for obtaining interior information of the object by transmitting and receiving ultrasonic waves enables image observation in real time and provides no exposure to radiation unlike other medical image technologies such as X-ray photography or RI (radio isotope) scintillation camera. Accordingly, ultrasonic imaging is utilized as an imaging technology at a high level of safety in a wide range of departments including not only fetal diagnosis in obstetrics but also gynecology, circulatory system, digestive system, etc.
The ultrasonic imaging is an imaging technology for generating images according to the following principle. Ultrasonic waves are reflected at the interface between regions having different acoustic impedances like the interface between structures. Therefore, by transmitting an ultrasonic beam into an object to be inspected such as a human body, receiving ultrasonic echoes generated within the object, and obtaining reflection points where the ultrasonic echoes are generated or reflection intensity, the outline of a structure (e.g., internal organs, diseased tissues, or the like) existing within the object can be extracted.
By the way, in order to generate ultrasonic images suitable for medical diagnosis, it is necessary to perform various kinds of image processing on the original image data acquired by receiving ultrasonic echoes. For example, there is generally performed such image processing as processing by DSC (digital scan converter) for converting a scan format from image data (sound ray data) in scan space (sound ray space) of the ultrasonic beam for scanning the object into image data in physical space, combining of plural frame images, sharpness enhancement processing (edge enhancement processing), graininess suppression processing (smoothing processing), or the like. International Application Publication WO00/20885 discloses an ultrasonic diagnostic imaging system for generating display images by correcting displacement between component images and then combining them. Further, Japanese Patent Application Publication JP-A-10-40371 discloses an image processing apparatus provided with a filter characteristic determining unit for calculating a local characteristic amount with respect to each pixel of interest in image data of an original image and determining characteristics of local filters based on the calculated characteristic amounts to output them.
Especially, in an ultrasonic image in which an object having an ununiform structure like a living body is imaged, there appears a pattern having bright parts and/or dark parts are scattered. Such a pattern is called as a speckle pattern, and the speckle pattern is generated, for example, by interference between ultrasonic echoes reflected from ununiform tissues existing within an internal organ or the like. The speckle pattern acts as a kind of noise, and thereby, the demonstrated outline of the structure or the like often becomes unclear. Accordingly, in order to generate an image suitable for medical diagnosis from such an original image, it is necessary to perform image processing including sharpness enhancement processing and graininess suppression processing on the acquired original image data. As such processing, specifically, averaging processing, median filtering processing, hysteresis smoothing processing, morphology processing and so on are known.
The morphology processing is image processing using elements called as structure elements relating to movement of the image and operations called as Mincowski sum and Mincowski difference. The Mincowski sum and Mincowski difference with functions “f” and “g” are defined by equations (1) and (2), respectively. In the following equations (1) to (4), “F” and “G” represent domains of “f” and “g”, respectively.
                              Mincowski          ⁢                                          ⁢                      sum            :                                                  ⁢                                          (                                  f                  ⊕                  g                                )                            ⁢                              (                x                )                                                    =                                            max                                                x                  -                  u                                ∈                F                                                    u              ∈              G                                ⁢                      {                                          f                ⁡                                  (                                      x                    -                    u                                    )                                            +                              g                ⁡                                  (                  u                  )                                                      }                                              (        1        )                                          Mincowski          ⁢                                          ⁢                      difference            :                                                  ⁢                                          (                                  f                  ⊖                  g                                )                            ⁢                              (                x                )                                                    =                              min                          u              ∈              G                                ⁢                      {                                          f                ⁡                                  (                                      x                    -                    u                                    )                                            -                              g                ⁡                                  (                  u                  )                                                      }                                              (        2        )            
The morphology processing includes four basic processing called as dilation, erosion, opening, and closing. The basic processing with respect to image function “f” by using structure element “gs” is determined by the following equations (3) to (6). In the equations (3) to (6), the function “g” is symmetric with respect to the point of origin.
                              Dilation          :                                          ⁢                                    (                              f                ⊕                                  g                  s                                            )                        ⁢                          (              x              )                                      =                                            max                                                x                  +                  u                                ∈                F                                                    u              ∈              G                                ⁢                      {                                          f                ⁡                                  (                                      x                    +                    u                                    )                                            +                              g                ⁡                                  (                  u                  )                                                      }                                              (        3        )                                          Erosion          :                                          ⁢                                    (                              f                ⊖                                  g                  s                                            )                        ⁢                          (              x              )                                      =                              min                          x              ∈              G                                ⁢                      {                                          f                ⁡                                  (                                      x                    +                    u                                    )                                            -                              g                ⁡                                  (                  u                  )                                                      }                                              (        4        )            Opening:fg=(f⊖gs)⊕g  (5)Closing:fg=(f⊕gs)⊖g  (6)
As shown in the equation (3), the dilation is processing of obtaining Mincowski sum of image function “f” moved by the structure element “gs”, and, intuitively, has a function of expanding the original image by searching for the maximum value within the mask defined based on the structure element and replacing the pixel value at the center of the mask area with the maximum value. Further, as shown in the equation (4), the erosion is processing of obtaining Mincowski difference of image function “f” moved by the structure element “gs”, and, intuitively, has a function of contracting the original image by searching for the minimum value within the mask and replacing the pixel value at the center of the mask area with the minimum value. Furthermore, the opening is processing of performing dilation after erosion, and has a function of removing convex portions, for example. Further, the closing is processing of performing erosion after dilation, and has a function of plugging concave portions, for example.
It is under study to extracting a structure from an ultrasonic image or improving the image quality by applying such morphology processing to ultrasonic image processing. Japanese Patent Application Publication JP-A-10-84286 discloses that edge lines are extracted by performing morphology processing as preprocessing in an apparatus for coding and decoding time-series data in order to make diagnoses efficiently. Further, Tsubai et al., “Control of Variable Structuring Element on Adaptive Mathematical Morphology for Boundary Enhancement of Ultrasound Images”, IEICE Transactions D-II, Vol. J86-D-II No. 6, pp. 895-907, June 2003 discloses that interface enhancement and speckle reduction are simultaneously performed by controlling the structure elements in the morphology processing.
By the way, generally in ultrasonic image processing, conversion of scan format and so on are performed on the original image data. However, by such conversion of scan format, image characteristics (e.g., frequency bands and so on) of the original image data are sometimes changed or lost. Accordingly, in the subsequent image processing like smoothing processing and edge enhancement processing including the morphology processing, it often occurs that characteristics of the original image data cannot be utilized. Further, also in the morphology processing, the following problem occurs. That is, the morphology processing has a function of smoothing a pattern smaller than the mask size which is used as a reference, and therefore, artifacts (virtual images) due to the mask size, i.e., the structure element are sometimes generated.